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      Skin dysbiosis and Cutibacterium acnes biofilm in inflammatory acne lesions of adolescents

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          Abstract

          Acne vulgaris is a common inflammatory disorder affecting more than 80% of young adolescents. Cutibacterium acnes plays a role in the pathogenesis of acne lesions, although the mechanisms are poorly understood. The study aimed to explore the microbiome at different skin sites in adolescent acne and the role of biofilm production in promoting the growth and persistence of C. acnes isolates. Microbiota analysis showed a significantly lower alpha diversity in inflammatory lesions (LA) than in non-inflammatory (NI) lesions of acne patients and healthy subjects (HS). Differences at the species level were driven by the overabundance of C. acnes on LA than NI and HS. The phylotype IA1 was more represented in the skin of acne patients than in HS. Genes involved in lipids transport and metabolism, as well as potential virulence factors associated with host-tissue colonization, were detected in all IA1 strains independently from the site of isolation. Additionally, the IA1 isolates were more efficient in early adhesion and biomass production than other phylotypes showing a significant increase in antibiotic tolerance. Overall, our data indicate that the site-specific dysbiosis in LA and colonization by virulent and highly tolerant C. acnes phylotypes may contribute to acne development in a part of the population, despite the universal carriage of the microorganism. Moreover, new antimicrobial agents, specifically targeting biofilm-forming C. acnes, may represent potential treatments to modulate the skin microbiota in acne.

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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            Roary: rapid large-scale prokaryote pan genome analysis

            Summary: A typical prokaryote population sequencing study can now consist of hundreds or thousands of isolates. Interrogating these datasets can provide detailed insights into the genetic structure of prokaryotic genomes. We introduce Roary, a tool that rapidly builds large-scale pan genomes, identifying the core and accessory genes. Roary makes construction of the pan genome of thousands of prokaryote samples possible on a standard desktop without compromising on the accuracy of results. Using a single CPU Roary can produce a pan genome consisting of 1000 isolates in 4.5 hours using 13 GB of RAM, with further speedups possible using multiple processors. Availability and implementation: Roary is implemented in Perl and is freely available under an open source GPLv3 license from http://sanger-pathogens.github.io/Roary Contact: roary@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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              eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses

              Abstract eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de
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                Author and article information

                Contributors
                enea.didomenico@uniroma1.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 December 2022
                6 December 2022
                2022
                : 12
                : 21104
                Affiliations
                [1 ]GRID grid.419467.9, ISNI 0000 0004 1757 4473, Microbiology and Virology, , IRCCS San Gallicano Institute, ; Rome, Italy
                [2 ]GRID grid.419467.9, ISNI 0000 0004 1757 4473, Cutaneous Physiopathology, , San Gallicano Dermatological Institute, IRCCS, ; Rome, Italy
                [3 ]Dipartimento di Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico Universitario “A. Gemelli” IRCSS, Rome, Italy
                [4 ]GRID grid.7841.a, Department of Biology and Biotechnology Charles Darwin, , Sapienza University of Rome, ; Rome, Italy
                [5 ]Biofilm Pharma SAS, Saint-Beauzire, France
                [6 ]GRID grid.8142.f, ISNI 0000 0001 0941 3192, Dipartimento di Scienze Biotecnologiche di Base, Cliniche Intensivologiche e Perioperatorie - Sezione di Microbiologia, , Università Cattolica del Sacro Cuore, ; Rome, Italy
                [7 ]GRID grid.419467.9, ISNI 0000 0004 1757 4473, Clinical Dermatology, , San Gallicano Dermatological Institute, IRCCS, ; Rome, Italy
                [8 ]GRID grid.419467.9, ISNI 0000 0004 1757 4473, Scientific Direction, , IRCCS San Gallicano Institute, ; Rome, Italy
                Article
                25436
                10.1038/s41598-022-25436-3
                9727105
                36473894
                98a05af5-6c3a-41e8-a226-9295e6bbd50f
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 25 July 2022
                : 29 November 2022
                Categories
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                © The Author(s) 2022

                Uncategorized
                microbiology,antimicrobials,biofilms,clinical microbiology,microbial communities
                Uncategorized
                microbiology, antimicrobials, biofilms, clinical microbiology, microbial communities

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